Advanced IoT and Machine Learning Techniques for Effective Heart Disease Diagnosis

The worldwide statistics of heart diseases are increasing; therefore, new strategies for the prevention and effective treatment are becoming important. The findings of this study seeks to develop complex solutions involving IoT and ML in increasing the efficiency of diagnosis of heart diseases. The study establishes an IoT based system for health monitoring to collect essential cardiovascular data using wearable sensors. The data is processed using more sophisticated methods of machine learning, and the forecasted results are potential heart diseases. The effectiveness of the proposed system is assessed by using the large dataset yielded by such diagnostic measures as accuracy, sensitivity, and specificity enhanced when compared to conventional approaches. The results stress the importance of the synergy between two often-discussed buzzwords, IoT and ML, to transform the diagnosis of heart diseases and hence, help create the future intelligent healthcare systems.